Specialized genetic algorithm for transmission network expansion planning considering reliability

Detalhes bibliográficos
Autor(a) principal: Garcés, Lina [UNESP]
Data de Publicação: 2009
Outros Autores: Romero, Rubén [UNESP]
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1109/ISAP.2009.5352832
http://hdl.handle.net/11449/71476
Resumo: This paper presents a methodology to solve the transmission network expansion planning problem (TNEP) considering reliability and uncertainty in the demand. The proposed methodology provides an optimal expansion plan that allows the power system to operate adequately with an acceptable level of reliability and in an enviroment with uncertainness. The reliability criterion limits the expected value of the reliability index (LOLE - Loss Of Load Expectation) of the expanded system. The reliability is evaluated for the transmission system using an analytical technique based in enumeration. The mathematical model is solved, in a efficient way, using a specialized genetic algorithm of Chu-Beasley modified. Detailed results from an illustrative example are presented and discussed. © 2009 IEEE.
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spelling Specialized genetic algorithm for transmission network expansion planning considering reliabilityGenetic algorithmMixed-integer non linear programmingReliabilityTransmission expansion planningAnalytical techniquesExpansion plansExpected valuesIllustrative examplesLoss of load expectationPower systemsReliability criterionReliability IndexTransmission network expansion planningTransmission systemsDynamic programmingElectric power transmissionElectric power transmission networksGenetic algorithmsInteger programmingIntelligent systemsLinearizationMathematical modelsOptimizationThis paper presents a methodology to solve the transmission network expansion planning problem (TNEP) considering reliability and uncertainty in the demand. The proposed methodology provides an optimal expansion plan that allows the power system to operate adequately with an acceptable level of reliability and in an enviroment with uncertainness. The reliability criterion limits the expected value of the reliability index (LOLE - Loss Of Load Expectation) of the expanded system. The reliability is evaluated for the transmission system using an analytical technique based in enumeration. The mathematical model is solved, in a efficient way, using a specialized genetic algorithm of Chu-Beasley modified. Detailed results from an illustrative example are presented and discussed. © 2009 IEEE.Department of Electrical Engineering Paulista State University - UNESP, Ilha Solteira, Sao Paulo, 15385-000Department of Electrical Engineering Paulista State University - UNESP, Ilha Solteira, Sao Paulo, 15385-000Universidade Estadual Paulista (Unesp)Garcés, Lina [UNESP]Romero, Rubén [UNESP]2014-05-27T11:24:34Z2014-05-27T11:24:34Z2009-12-09info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObjecthttp://dx.doi.org/10.1109/ISAP.2009.53528322009 15th International Conference on Intelligent System Applications to Power Systems, ISAP '09.http://hdl.handle.net/11449/7147610.1109/ISAP.2009.53528322-s2.0-76549094515Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPeng2009 15th International Conference on Intelligent System Applications to Power Systems, ISAP '09info:eu-repo/semantics/openAccess2024-07-04T19:11:44Zoai:repositorio.unesp.br:11449/71476Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T20:08:07.476983Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Specialized genetic algorithm for transmission network expansion planning considering reliability
title Specialized genetic algorithm for transmission network expansion planning considering reliability
spellingShingle Specialized genetic algorithm for transmission network expansion planning considering reliability
Garcés, Lina [UNESP]
Genetic algorithm
Mixed-integer non linear programming
Reliability
Transmission expansion planning
Analytical techniques
Expansion plans
Expected values
Illustrative examples
Loss of load expectation
Power systems
Reliability criterion
Reliability Index
Transmission network expansion planning
Transmission systems
Dynamic programming
Electric power transmission
Electric power transmission networks
Genetic algorithms
Integer programming
Intelligent systems
Linearization
Mathematical models
Optimization
title_short Specialized genetic algorithm for transmission network expansion planning considering reliability
title_full Specialized genetic algorithm for transmission network expansion planning considering reliability
title_fullStr Specialized genetic algorithm for transmission network expansion planning considering reliability
title_full_unstemmed Specialized genetic algorithm for transmission network expansion planning considering reliability
title_sort Specialized genetic algorithm for transmission network expansion planning considering reliability
author Garcés, Lina [UNESP]
author_facet Garcés, Lina [UNESP]
Romero, Rubén [UNESP]
author_role author
author2 Romero, Rubén [UNESP]
author2_role author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv Garcés, Lina [UNESP]
Romero, Rubén [UNESP]
dc.subject.por.fl_str_mv Genetic algorithm
Mixed-integer non linear programming
Reliability
Transmission expansion planning
Analytical techniques
Expansion plans
Expected values
Illustrative examples
Loss of load expectation
Power systems
Reliability criterion
Reliability Index
Transmission network expansion planning
Transmission systems
Dynamic programming
Electric power transmission
Electric power transmission networks
Genetic algorithms
Integer programming
Intelligent systems
Linearization
Mathematical models
Optimization
topic Genetic algorithm
Mixed-integer non linear programming
Reliability
Transmission expansion planning
Analytical techniques
Expansion plans
Expected values
Illustrative examples
Loss of load expectation
Power systems
Reliability criterion
Reliability Index
Transmission network expansion planning
Transmission systems
Dynamic programming
Electric power transmission
Electric power transmission networks
Genetic algorithms
Integer programming
Intelligent systems
Linearization
Mathematical models
Optimization
description This paper presents a methodology to solve the transmission network expansion planning problem (TNEP) considering reliability and uncertainty in the demand. The proposed methodology provides an optimal expansion plan that allows the power system to operate adequately with an acceptable level of reliability and in an enviroment with uncertainness. The reliability criterion limits the expected value of the reliability index (LOLE - Loss Of Load Expectation) of the expanded system. The reliability is evaluated for the transmission system using an analytical technique based in enumeration. The mathematical model is solved, in a efficient way, using a specialized genetic algorithm of Chu-Beasley modified. Detailed results from an illustrative example are presented and discussed. © 2009 IEEE.
publishDate 2009
dc.date.none.fl_str_mv 2009-12-09
2014-05-27T11:24:34Z
2014-05-27T11:24:34Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/conferenceObject
format conferenceObject
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1109/ISAP.2009.5352832
2009 15th International Conference on Intelligent System Applications to Power Systems, ISAP '09.
http://hdl.handle.net/11449/71476
10.1109/ISAP.2009.5352832
2-s2.0-76549094515
url http://dx.doi.org/10.1109/ISAP.2009.5352832
http://hdl.handle.net/11449/71476
identifier_str_mv 2009 15th International Conference on Intelligent System Applications to Power Systems, ISAP '09.
10.1109/ISAP.2009.5352832
2-s2.0-76549094515
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2009 15th International Conference on Intelligent System Applications to Power Systems, ISAP '09
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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